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Jenna Wiens

29 papers · 2010–2026 · 8 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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+9 more ↓ πŸ—ΊοΈ Taxonomy Completionist (56) πŸƒ Academic Marathon Β· Full 🌍 Conference Polyglot Β· Silver πŸŒ‰ Interdisciplinary Bridge Β· Silver 🐣 Hot Topic Early Bird
πŸ† Keyword Champion (2) 🧭 Keyword Pioneer πŸ—ƒοΈ Keyword Collector (149) πŸ“ˆ Trend Setter πŸ’Ž Century Club Β· Bronze πŸ”₯ Unstoppable Β· Bronze ⚑ Prolific Year Β· Productive ❓ The Questioner 🌈 Renaissance Researcher (9)

Venues

MLHC (9) NeurIPS (6) AAAI (5) AISTATS (4) ICML (2) ECCV (1) IJCAI (1) JMLR (1)

Top co-authors

Shengpu Tang (5) Michael Sjoding (4) Maggie Makar (4) Michael W. Sjoding (4) Trenton Chang (4) Jiaxuan Wang (4) Sarah Jabbour (3) Jeeheh Oh (3) Danai Koutra (2) Joyce Lee (2)

Research topics

Machine Learning (23) Artificial Intelligence (14) Core AI (13) Core Methods (11) Deep Learning (10) Learning Types Β· Machine Learning (9) Optimization & Theory (9) Healthcare & Medicine (8) Clinical (8) Application Areas (7) Architectures (5) Reinforcement Learning (4) Methods (4) Learning Types Β· Deep Learning (3) Data Science & Analytics (2)

Keywords

patient risk stratification (4) reinforcement learning (3) risk stratification (3) clinical time series (2) graph neural network (2) deep learning (2) spurious correlation (2) survival analysis (2) domain adaptation (2) convolutional neural network (2) medical imaging (2) domain knowledge (2) off-policy evaluation (2) mortality prediction (2) shortcut learning (2) causal inference (2) algorithmic fairness (1) representation learning (1) feature learning (1) multi-task learning (1)

Papers

A Course Correction in Steerability Evaluation: Revealing Miscalibration and Side Effects in LLMs AAAI 2026 Measuring Model Performance in the Presence of an Intervention AAAI 2026 Learning Laplacian Positional Encodings for Heterophilous Graphs AISTATS 2025 Understanding GNNs and Homophily in Dynamic Node Classification AISTATS 2025 DEPICT: Diffusion-Enabled Permutation Importance for Image Classification Tasks ECCV 2024 From Biased Selective Labels to Pseudo-Labels: An Expectation-Maximization Framework for Learning from Biased Decisions ICML 2024 Learning to Rank for Optimal Treatment Allocation Under Resource Constraints AISTATS 2024 Who’s Gaming the System? A Causally-Motivated Approach for Detecting Strategic Adaptation NeurIPS 2024 Counterfactual-Augmented Importance Sampling for Semi-Offline Policy Evaluation NeurIPS 2023 Forecasting with Sparse but Informative Variables: A Case Study in Predicting Blood Glucose AAAI 2023 Updating Clinical Risk Stratification Models Using Rank-Based Compatibility: Approaches for Evaluating and Optimizing Clinician-Model Team Performance MLHC 2023 Disparate Censorship & Undertesting: A Source of Label Bias in Clinical Machine Learning MLHC 2022 Learning Concept Credible Models for Mitigating Shortcuts NeurIPS 2022 Leveraging Factored Action Spaces for Efficient Offline Reinforcement Learning in Healthcare NeurIPS 2022 A Hierarchical Approach to Multi-Event Survival Analysis AAAI 2021 Estimating Calibrated Individualized Survival Curves with Deep Learning AAAI 2021 Mind the Performance Gap: Examining Dataset Shift During Prospective Validation MLHC 2021 Model Selection for Offline Reinforcement Learning: Practical Considerations for Healthcare Settings MLHC 2021 Shapley Flow: A Graph-based Approach to Interpreting Model Predictions AISTATS 2021 Clinician-in-the-Loop Decision Making: Reinforcement Learning with Near-Optimal Set-Valued Policies ICML 2020 Deep Learning Applied to Chest X-Rays: Exploiting and Preventing Shortcuts MLHC 2020 Deep Reinforcement Learning for Closed-Loop Blood Glucose Control MLHC 2020 Advocacy Learning: Learning through Competition and Class-Conditional Representations IJCAI 2019 Relaxed Parameter Sharing: Effectively Modeling Time-Varying Relationships in Clinical Time-Series MLHC 2019 A Domain Guided CNN Architecture for Predicting Age from Structural Brain Images MLHC 2018 Learning to Exploit Invariances in Clinical Time-Series Data using Sequence Transformer Networks MLHC 2018 Patient Risk Stratification with Time-Varying Parameters: A Multitask Learning Approach JMLR 2016 Patient Risk Stratification for Hospital-Associated C. diff as a Time-Series Classification Task NeurIPS 2012 Active Learning Applied to Patient-Adaptive Heartbeat Classification NeurIPS 2010